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dev55acc-ai

Website Content Crawler MCP Server

by dev55acc-ai

crawl_website

Extract text content from websites by crawling pages, with support for static and JavaScript-rendered sites. Specify URL, max pages, and crawler type to get structured JSON results.

Instructions

Crawl a website and extract page content by running the apify/website-content-crawler actor. Returns a fixed-shape envelope: {status, run:{id,status}, page_count, pages:[{url,title,text}]}. Requires APIFY_TOKEN in the environment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to crawl (http/https)
maxPagesNoMaximum pages to crawl, capped at 50 (default 10)
crawlerTypeNocheerio = fast/static and cheaper; playwright:chrome = JS-rendered sites (default cheerio)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It reveals that this is an external actor invocation, requires APIFY_TOKEN, and returns a fixed envelope, which gives the agent an honest model of what happens. It does not detail cost/time/side effects, but the core execution model is disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact sentences deliver purpose, mechanism, return shape, and a prerequisite without wasted words. The key purpose is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The hard-coded return envelope compensate for the absent output schema, and the auth requirement is noted. It doesn't cover failure modes or performance expectations, but the essentials for calling and understanding the result are present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all three parameters. The description adds no parameter-level meaning, but the baseline 3 is appropriate because it does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise action ('Crawl a website and extract page content') plus the underlying mechanism (running the apify/website-content-crawler actor), so its purpose is clear even without siblings. It also states the return shape to help the tool be disambiguated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys when the tool is appropriate: when a website needs to be crawled and page text extracted. It names the required environment token and return envelope, but does not explicitly state when not to use or what alternatives might apply.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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